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To manage parallel rules, the inference engine uses an inference table to compute final fuzzy set. It computes, for each variable, its conclusion fuzzy set and combines all the conclusion fuzzy sets in accordance with rule operator combination and aggregation and parallel principles.
Assume the following rules and facts.
Rule 1 | : | IF | X is ![]() |
Y is ![]() |
THEN | W is ![]() |
|
Rule 2 | : | IF | X is ![]() |
Z is ![]() |
THEN | W is ![]() |
|
Facts | : | X is ![]() |
Y is ![]() |
Z is ![]() |
|||
Conclusion | : | W is ![]() |
The algorithm
is applied for each no parallel variable and
(in this case n=2), for each parallel variable as shows the following
inference table :
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with
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